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https://issues.apache.org/jira/browse/SPARK-26378?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Bruce Robbins updated SPARK-26378:
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Description:
A recent change significantly slowed the queries of wide CSV tables. For
example, queries against a 6000 column table slowed by 45-48% when queried with
a single executor.
The [PR for
SPARK-26151|https://github.com/apache/spark/commit/11e5f1bcd49eec8ab4225d6e68a051b5c6a21cb2]
changed FailureSafeParser#toResultRow such that the returned function
recreates every row, even when the associated input record has no parsing
issues and the user specified no corrupt record field in his/her schema. This
extra processing is responsible for the slowdown.
The change to FailureSafeParser also impacted queries of wide JSON tables as
well.
I propose that a row should be recreated only if there is a parsing error or
columns need to be shifted due to the existence of a corrupt column field in
the user-supplied schema. Otherwise, the row should be used as-is.
was:
A recent change significantly slowed the queries of wide CSV tables. For
example, queries against a 6000 column table slowed by 45-48% when queried with
a single executor.
The [PR for
SPARK-26151|https://github.com/apache/spark/commit/11e5f1bcd49eec8ab4225d6e68a051b5c6a21cb2]
changed FailureSafeParser#toResultRow such that the returned function
recreates every row, even when the associated input record has no parsing
issues and the user specified no corrupt record field in his/her schema. This
extra processing is responsible for the slowdown.
I propose that a row should be recreated only if there is a parsing error or
columns need to be shifted due to the existence of a corrupt column field in
the user-supplied schema. Otherwise, the row should be used as-is.
> Queries of wide CSV/JSON data slowed after SPARK-26151
> ------------------------------------------------------
>
> Key: SPARK-26378
> URL: https://issues.apache.org/jira/browse/SPARK-26378
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Bruce Robbins
> Priority: Major
>
> A recent change significantly slowed the queries of wide CSV tables. For
> example, queries against a 6000 column table slowed by 45-48% when queried
> with a single executor.
>
> The [PR for
> SPARK-26151|https://github.com/apache/spark/commit/11e5f1bcd49eec8ab4225d6e68a051b5c6a21cb2]
> changed FailureSafeParser#toResultRow such that the returned function
> recreates every row, even when the associated input record has no parsing
> issues and the user specified no corrupt record field in his/her schema. This
> extra processing is responsible for the slowdown.
> The change to FailureSafeParser also impacted queries of wide JSON tables as
> well.
> I propose that a row should be recreated only if there is a parsing error or
> columns need to be shifted due to the existence of a corrupt column field in
> the user-supplied schema. Otherwise, the row should be used as-is.
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